Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add chuancyzhang/deepseek-cowork --skill sector_rotation_radar_skillgit clone --depth 1 https://github.com/chuancyzhang/deepseek-coworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/sector_rotation_radar_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/sector_rotation_radar_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/sector_rotation_radar_skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/sector_rotation_radar_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/sector_rotation_radar_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.01604 |
| Opus 5.5 | $0.00024 | $0.00642 |
| Sonnet 5.5 | $0.00012 | $0.00321 |
| Haiku 4.5 | $0.00006 | $0.00160 |
Grade A, and why
sector_rotation_radar_skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
83% identical to breakout_candidate_finder_skill — 203 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sector Rotation Radar Skill
数据依赖与执行前置条件
推荐使用万得 wind-mcp-skill 获取底层数据。执行前先检查本地是否已有 wind-mcp-skill；若没有，提示用户安装：
Cowork 适配：所需子 Skill 已随
wind-aifinmarket固定快照内置，不执行安装或在线更新命令。
技能定位
本技能用于把“哪些板块在变强、哪些板块在掉队、资金正在从哪里流向哪里、轮动是否具有持续性”整理成一份结构化判断。输出重点不是简单罗列涨跌幅排名，而是帮助使用者识别市场主线、判断风格切换是否成立，并给出后续应重点跟踪的方向。
执行流程
Step 1：确认观察市场、时间窗口与判断目标
先确认本次判断覆盖的市场范围、时间窗口和使用目的：
- 是看 A 股、港股、美股，还是跨市场比较
- 是观察近 1 日、近 1 周、近 1 月，还是更长周期
- 是为了盘后复盘、周度策略更新，还是寻找下一阶段主线
- 用户更关心短线强弱切换，还是中期风格迁移
若用户未说明，默认以“当前市场最近一周至一个月的板块轮动情况”为主，并兼顾短期和中期两个层次。
Step 2：建立板块强弱分层框架
先把市场中的主要板块、行业或主题分层整理出来，重点观察：
- 近期表现最强的方向是否集中在少数板块
- 强势板块内部是一致走强，还是仅由少数龙头带动
- 弱势板块是持续走弱，还是处于止跌修复阶段
- 周期、成长、消费、金融、防御等风格的相对强弱是否在变化
这一阶段的目标是先回答“强弱分布如何”，而不是急于给出轮动结论。
Step 3：识别资金切换与风格迁移线索
在强弱分层明确后，进一步判断资金是否正在发生实质性迁移，重点包括：
- 资金是在高位主线内部做高低切换，还是跨风格流动
- 强势板块上涨是否伴随成交活跃度提升
- 市场偏好是否从防守转向进攻，或从进攻切回防守
- 板块轮动是普涨环境下的扩散，还是存量博弈下的轮番接力
要把“价格表现”与“资金承接”结合起来看，避免把单日异动误判为趋势性轮动。
Step 4：解释轮动背后的驱动因素
在确认轮动迹象后，分析驱动原因，优先从以下几类因素拆解：
- 宏观预期变化对风格偏好的影响
- 产业趋势、业绩预期或估值修复带来的催化
- 政策、监管或事件刺激对某些板块的阶段性提振
- 机构调仓、被动资金再平衡或交易拥挤后的再分配
若多个因素共同作用，应区分主驱动和次驱动，避免把所有因素并列堆砌。
Step 5：判断轮动的持续性与传导方向
进一步判断这次轮动属于哪一类：
- 新主线启动
- 老主线修复
- 强势主题内部扩散
- 高低切换下的补涨行情
- 纯交易性短线扰动
同时说明轮动下一步更可能朝哪个方向传导：
- 龙头继续强化
- 中军和二线标的补涨
- 上游传导到下游，或下游反馈到上游
- 风格从局部扩散到更广泛市场
Step 6：形成板块轮动判断成稿
最终输出应让使用者快速知道当前市场主线在哪里、轮动是否扎实、哪些方向值得继续看、哪些方向不宜追高。成稿只保留结论、证据和跟踪框架，不展示内部检索过程。
输出结构
{市场范围}板块轮动雷达（{YYYY-MM-DD}）
一、30 秒结论
- 当前最强主线：{板块或主题}
- 当前最明显的轮动方向：{内容}
- 风格判断：{偏进攻 / 偏防守 / 震荡切换}
- 持续性判断：{较强 / 一般 / 偏弱}
二、板块强弱快照
| 板块/主题 | 当前状态 | 强弱变化 | 轮动性质 | 备注 |
|---|---|---|---|---|
| {板块1} | {领涨 / 修复 / 回落} | {增强 / 持平 / 转弱} | {主升 / 补涨 / 轮退} | {说明} |
| {板块2} | {状态} | {变化} | {性质} | {说明} |
| {板块3} | {状态} | {变化} | {性质} | {说明} |
三、资金切换与风格迁移
- 资金流向概括：{内容}
- 风格切换线索：{内容}
- 内部高低切换情况：{内容}
四、轮动驱动拆解
- 主驱动：{内容}
- 次驱动：{内容}
- 短期扰动因素：{内容}
五、后续传导路径
- 更可能继续强化的方向：{内容}
- 可能出现补涨的方向：{内容}
- 需要警惕的轮退方向：{内容}
六、跟踪清单
- {观察点 1}
- {观察点 2}
- {观察点 3}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 141 lines · 61 tokens per session scan A bbb1fdc1bf58
sector_rotation_radar_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 1,604 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 83% identical to breakout_candidate_finder_skill, differing in 203 lines, and is treated as a copy.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
twitter-reader
Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
energy-procurement
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…
airdrop-hunting-guide
Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.
recipe-daily-pnl-report
Generate a daily profit and loss summary from trades and balances.